Saved in:
| Main Authors: | Yu, Lu, Chang, Zheng, Liang, Ying-Chang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.04936 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks
by: Yu, Lu, et al.
Published: (2024)
by: Yu, Lu, et al.
Published: (2024)
AIGC-assisted Federated Learning for Edge Intelligence: Architecture Design, Research Challenges and Future Directions
by: Qiang, Xianke, et al.
Published: (2025)
by: Qiang, Xianke, et al.
Published: (2025)
Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
by: Qiang, Xianke, et al.
Published: (2024)
by: Qiang, Xianke, et al.
Published: (2024)
Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning
by: Qiang, Xianke, et al.
Published: (2025)
by: Qiang, Xianke, et al.
Published: (2025)
TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks
by: Qiang, Xianke, et al.
Published: (2026)
by: Qiang, Xianke, et al.
Published: (2026)
Age-Based Device Selection and Transmit Power Optimization in Over-the-Air Federated Learning
by: Liu, Jingyuan, et al.
Published: (2025)
by: Liu, Jingyuan, et al.
Published: (2025)
Semantic-Aware Cooperative Communication and Computation Framework in Vehicular Networks
by: Zhang, Jingbo, et al.
Published: (2025)
by: Zhang, Jingbo, et al.
Published: (2025)
Federated Learning for Tabular Data using TabNet: A Vehicular Use-Case
by: Lindskog, William, et al.
Published: (2024)
by: Lindskog, William, et al.
Published: (2024)
Mobility-Aware Federated Self-supervised Learning in Vehicular Network
by: Gu, Xueying, et al.
Published: (2024)
by: Gu, Xueying, et al.
Published: (2024)
An Operator Splitting View of Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2021)
by: Malekmohammadi, Saber, et al.
Published: (2021)
Efficient Split Federated Learning for Large Language Models over Communication Networks
by: Zhao, Kai, et al.
Published: (2025)
by: Zhao, Kai, et al.
Published: (2025)
Separate Aggregation of Split Network for Personalized Federated Learning
by: Kang, Yunseok, et al.
Published: (2026)
by: Kang, Yunseok, et al.
Published: (2026)
Towards Secure and Efficient Data Scheduling for Vehicular Social Networks
by: Xia, Youhua, et al.
Published: (2024)
by: Xia, Youhua, et al.
Published: (2024)
SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning
by: Shan, Yimeng, et al.
Published: (2026)
by: Shan, Yimeng, et al.
Published: (2026)
Deep Neural Network-Driven Adaptive Filtering
by: Wang, Qizhen, et al.
Published: (2025)
by: Wang, Qizhen, et al.
Published: (2025)
Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Network
by: Tu, Haoyu, et al.
Published: (2024)
by: Tu, Haoyu, et al.
Published: (2024)
FedsLLM: Federated Split Learning for Large Language Models over Communication Networks
by: Zhao, Kai, et al.
Published: (2024)
by: Zhao, Kai, et al.
Published: (2024)
Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks
by: Chen, Tan, et al.
Published: (2024)
by: Chen, Tan, et al.
Published: (2024)
Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
by: Papageorgiou, Yiannis, et al.
Published: (2026)
by: Papageorgiou, Yiannis, et al.
Published: (2026)
Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks
by: HaghighiFard, M. Saeid, et al.
Published: (2025)
by: HaghighiFard, M. Saeid, et al.
Published: (2025)
Federated Contrastive Learning for Personalized Semantic Communication
by: Wang, Yining, et al.
Published: (2024)
by: Wang, Yining, et al.
Published: (2024)
Targeted Attacks and Defenses for Distributed Federated Learning in Vehicular Networks
by: Demir, Utku, et al.
Published: (2025)
by: Demir, Utku, et al.
Published: (2025)
Communication and Computation Efficient Split Federated Learning in O-RAN
by: Gu, Shunxian, et al.
Published: (2025)
by: Gu, Shunxian, et al.
Published: (2025)
Ampere: Communication-Efficient and High-Accuracy Split Federated Learning
by: Zhang, Zihan, et al.
Published: (2025)
by: Zhang, Zihan, et al.
Published: (2025)
FedLion: Faster Adaptive Federated Optimization with Fewer Communication
by: Tang, Zhiwei, et al.
Published: (2024)
by: Tang, Zhiwei, et al.
Published: (2024)
mixEEG: Enhancing EEG Federated Learning for Cross-subject EEG Classification with Tailored mixup
by: Liu, Xuan-Hao, et al.
Published: (2025)
by: Liu, Xuan-Hao, et al.
Published: (2025)
Federated Learning with Enhanced Privacy via Model Splitting and Random Client Participation
by: Li, Yiwei, et al.
Published: (2025)
by: Li, Yiwei, et al.
Published: (2025)
VoI-Driven Joint Optimization of Control and Communication in Vehicular Digital Twin Network
by: Lei, Lei, et al.
Published: (2025)
by: Lei, Lei, et al.
Published: (2025)
An Efficient Federated Learning Framework for Training Semantic Communication System
by: Nguyen, Loc X., et al.
Published: (2023)
by: Nguyen, Loc X., et al.
Published: (2023)
FSSC: Federated Learning of Transformer Neural Networks for Semantic Image Communication
by: Yan, Yuna, et al.
Published: (2024)
by: Yan, Yuna, et al.
Published: (2024)
Federated Split Learning with Improved Communication and Storage Efficiency
by: Mu, Yujia, et al.
Published: (2025)
by: Mu, Yujia, et al.
Published: (2025)
Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection
by: HaghighiFard, M. Saeid, et al.
Published: (2024)
by: HaghighiFard, M. Saeid, et al.
Published: (2024)
Non-Federated Multi-Task Split Learning for Heterogeneous Sources
by: Zheng, Yilin, et al.
Published: (2024)
by: Zheng, Yilin, et al.
Published: (2024)
SplitFedZip: Learned Compression for Data Transfer Reduction in Split-Federated Learning
by: Shiranthika, Chamani, et al.
Published: (2024)
by: Shiranthika, Chamani, et al.
Published: (2024)
ELSA: Efficient LLM-Centric Split Aggregation for Privacy-Aware Hierarchical Federated Learning over the Network Edge
by: Yang, Xiaohong, et al.
Published: (2026)
by: Yang, Xiaohong, et al.
Published: (2026)
Federated Learning in NTNs: Design, Architecture and Challenges
by: Farajzadeh, Amin, et al.
Published: (2025)
by: Farajzadeh, Amin, et al.
Published: (2025)
AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
by: Lin, Zheng, et al.
Published: (2024)
by: Lin, Zheng, et al.
Published: (2024)
Personalized Hierarchical Split Federated Learning in Wireless Networks
by: Pervej, Md-Ferdous, et al.
Published: (2024)
by: Pervej, Md-Ferdous, et al.
Published: (2024)
RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations
by: Xue, Chang, et al.
Published: (2025)
by: Xue, Chang, et al.
Published: (2025)
Improving Pattern Recognition of Scheduling Anomalies through Structure-Aware and Semantically-Enhanced Graphs
by: Lyu, Ning, et al.
Published: (2025)
by: Lyu, Ning, et al.
Published: (2025)
Similar Items
-
Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks
by: Yu, Lu, et al.
Published: (2024) -
AIGC-assisted Federated Learning for Edge Intelligence: Architecture Design, Research Challenges and Future Directions
by: Qiang, Xianke, et al.
Published: (2025) -
Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
by: Qiang, Xianke, et al.
Published: (2024) -
Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning
by: Qiang, Xianke, et al.
Published: (2025) -
TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks
by: Qiang, Xianke, et al.
Published: (2026)